EE 545 Image Processing

Image formation, Binary image processing, Mathematical morphology, Region segmentation, Edge detection, Texture analysis, Shape recognition, Color spaces,Optics, Image enhancement, Image filtering and restoration, Image data compression.

EE 546 Pattern Recognition

Feature selection: Space transformations; Karhunen-Loeve expansion; various distance measures. Supervised learning: Discriminant functions; linear and nonlinear training algorithms; statistical parametric and nonparametric methods. Nonsupervised learning: Clustering with known or unknown number of classes.Classification by neural networks.

EE 547 Computer Vision

Properties of light, human vision, introduction to color image processing,introduction to multi-sensor images, extraction of structural features from images, recognition methods for computer vision, image sequences, optical flow and motion.

EE 503 Mathematics for Operations Research and Optimization

Groups and fields, vector spaces, Linear transformations, Gauss-Jordan pivoting, Gram-Schmidt procedure, unitary space. Hyperplanes, convex polyhedron, Linear inequalities, Tucker’s theorem for positive solutions, Minkowski’s theorem, Eigenvector-eigenvalue problem, definiteness, Jordan Canonical form theorem; Optimization theory on Rn:Constrained minimization problem, linear programming problem,Lagrange Multiplier Theorem, Kuhn-Tucker Conditions for Inequality constraints,convex programming.

EE 104 Introduction to Programming in Electrical Engineering

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